stream-chain

Automates multi-step streaming agent workflows with sequential context propagation.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/KingOfTheAce2/project-gouda --skill stream-chain-kingoftheace2
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: stream-chain
Source: https://github.com/KingOfTheAce2/project-gouda/tree/main/.claude/skills/stream-chain
Command: npx skills add https://github.com/KingOfTheAce2/project-gouda --skill stream-chain-kingoftheace2

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires claude-flow.

What problem does it solve?

This Skill eliminates the manual effort of stitching together outputs from multiple AI agents, allowing you to create complex, sequential workflows where each step automatically feeds into the next. It streamlines multi-stage data processing and development tasks.

Core Features & Use Cases

  • Custom Chains: Define and execute your own sequence of prompts for maximum flexibility.
  • Predefined Pipelines: Utilize battle-tested workflows for common tasks like analysis, refactoring, or testing.
  • Sequential Context Flow: Each agent receives the complete output of the previous step as its context, enabling sophisticated transformations.
  • Use Case: Automate a code refactoring process. First, identify code smells. Second, create a refactoring plan. Third, apply refactoring to top priorities. Fourth, verify behavior. Each step builds on the last, delivering a fully refactored and validated codebase.

Quick Start

Run a custom chain to "Write a user authentication function", then "Add input validation and error handling", and finally "Create unit tests with edge cases".

Frequently Asked Questions about stream-chain

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate multi-step workflows where each AI agent builds on the previous output?

Multi-step workflows chain sequential AI prompts so each agent receives the complete output of the prior step as context. stream-chain orchestrates this automatically, eliminating manual stitching of agent outputs and enabling complex transformations like code refactoring, data analysis, and testing pipelines where each phase depends on the last.

Can I use predefined workflows or do I have to write custom prompts?

stream-chain supports both modes. Run mode lets you define custom prompt sequences with minimum two prompts for flexibility. Pipeline mode provides battle-tested predefined workflows for common tasks like code analysis, refactoring, and testing, so you choose between full control or templated automation.

What's the best way to automate code refactoring with sequential validation?

Chain multiple prompts where the first identifies code smells, the second creates a refactoring plan, the third applies changes to priorities, and the fourth verifies behavior. stream-chain propagates context through each step, so later agents see prior analysis and decisions, delivering a fully refactored and validated codebase end-to-end.

Does stream-chain support streaming progress updates and configurable timeouts?

Yes. stream-chain exposes --verbose, --timeout, and --debug options alongside streaming progress and results output, enabling real-time monitoring of multi-agent workflows and control over execution time and debugging depth.

What does stream-chain require as a dependency?

stream-chain depends on claude-flow for orchestration. You must have claude-flow available to run custom chains or predefined pipelines that sequence multiple AI agents.

Can I use stream-chain for security auditing and data transformation tasks?

Yes. Beyond code refactoring and testing, stream-chain applies to security auditing, data transformation, code analysis, and other sequential automation tasks where each step consumes and builds on prior outputs.